Search strategy switching: an alternative to increased backtracking

Test generation algorithms use search strategies to control decision making whenever the algorithms encounter a choice of a signal value or action. The authors´ study of traditional search strategies used in automatic test pattern generation (ATPG) has led to the observation that no single strategy is superior for all faults in a circuit or all circuits. Further experimentation led to the conclusion that a combination of search strategies provides better fault coverage and/or faster ATPG for a given backtrack limit. Instead of using just one strategy to the backtrack limit, a primary strategy is used for the first half of the backtrack limit, and then a secondary strategy is used for the second half. The authors present an ATPG cost model based on the number of test generation events. They use this model to explain why search strategy switching is faster and show experimental evidence to verify the search strategy switching theory. The experiments were performed with the ISCAS circuits and the authors´ implementation of the FAN algorithm